Fix SpatialData table access and and fix getting full key names

src/squidpy/_constants/_pkg_constants.py

@@ -198,8 +198,18 @@ def _sort_haystack(
     class obsp:
         @classmethod
         def spatial_dist(cls, value: str | None = None) -> str:
-            return f"{Key.obsm.spatial}_distances" if value is None else f"{value}_distances"
+            if value is None:
+                return f"{Key.obsm.spatial}_distances"
+            # Handle case where suffix is already present
+            if value.endswith("_distances"):
+                return value
+            return f"{value}_distances"
 
         @classmethod
         def spatial_conn(cls, value: str | None = None) -> str:
-            return f"{Key.obsm.spatial}_connectivities" if value is None else f"{value}_connectivities"
+            if value is None:
+                return f"{Key.obsm.spatial}_connectivities"
+            # Handle case where suffix is already present
+            if value.endswith("_connectivities"):
+                return value
+            return f"{value}_connectivities"

src/squidpy/gr/_ligrec.py

@@ -642,6 +642,7 @@ def ligrec(
     copy: bool = False,
     key_added: str | None = None,
     gene_symbols: str | None = None,
+    table_key: str = "table",
     **kwargs: Any,
 ) -> Mapping[str, pd.DataFrame] | None:
     """
@@ -654,13 +655,20 @@ def ligrec(
     %(PT_test.parameters)s
     gene_symbols
         Key in :attr:`anndata.AnnData.var` to use instead of :attr:`anndata.AnnData.var_names`.
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
     %(ligrec_test_returns)s
     """  # noqa: D400
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     with _genesymbols(adata, key=gene_symbols, use_raw=use_raw, make_unique=False):
         return (  # type: ignore[no-any-return]
             PermutationTest(adata, use_raw=use_raw)

src/squidpy/gr/_nhood.py

@@ -146,6 +146,7 @@ def nhood_enrichment(
     n_jobs: int | None = None,
     backend: str = "loky",
     show_progress_bar: bool = True,
+    table_key: str = "table",
 ) -> NhoodEnrichmentResult | None:
     """
     Compute neighborhood enrichment by permutation test.
@@ -161,6 +162,9 @@ def nhood_enrichment(
     %(seed)s
     %(copy)s
     %(parallelize)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -172,7 +176,11 @@ def nhood_enrichment(
         - :attr:`anndata.AnnData.uns` ``['{cluster_key}_nhood_enrichment']['count']`` - the enrichment count.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     connectivity_key = Key.obsp.spatial_conn(connectivity_key)
     _assert_categorical_obs(adata, cluster_key)
     _assert_connectivity_key(adata, connectivity_key)
@@ -239,6 +247,7 @@ def centrality_scores(
     n_jobs: int | None = None,
     backend: str = "loky",
     show_progress_bar: bool = False,
+    table_key: str = "table",
 ) -> pd.DataFrame | None:
     """
     Compute centrality scores per cluster or cell type.
@@ -260,6 +269,9 @@ def centrality_scores(
     %(conn_key)s
     %(copy)s
     %(parallelize)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -269,7 +281,11 @@ def centrality_scores(
           as mentioned above.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     connectivity_key = Key.obsp.spatial_conn(connectivity_key)
     _assert_categorical_obs(adata, cluster_key)
     _assert_connectivity_key(adata, connectivity_key)
@@ -333,6 +349,7 @@ def interaction_matrix(
     normalized: bool = False,
     copy: bool = False,
     weights: bool = False,
+    table_key: str = "table",
 ) -> NDArrayA | None:
     """
     Compute interaction matrix for clusters.
@@ -347,6 +364,9 @@ def interaction_matrix(
     %(copy)s
     weights
         Whether to use edge weights or binarize.
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -357,7 +377,11 @@ def interaction_matrix(
         - :attr:`anndata.AnnData.uns` ``['{cluster_key}_interactions']`` - the interaction matrix.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     connectivity_key = Key.obsp.spatial_conn(connectivity_key)
     _assert_categorical_obs(adata, cluster_key)
     _assert_connectivity_key(adata, connectivity_key)

src/squidpy/gr/_ppatterns.py

@@ -62,6 +62,7 @@ def spatial_autocorr(
     n_jobs: int | None = None,
     backend: str = "loky",
     show_progress_bar: bool = True,
+    table_key: str = "table",
 ) -> pd.DataFrame | None:
     """
     Calculate Global Autocorrelation Statistic (Moran’s I  or Geary's C).
@@ -107,6 +108,9 @@ def spatial_autocorr(
     %(seed)s
     %(copy)s
     %(parallelize)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -129,7 +133,11 @@ def spatial_autocorr(
         - :attr:`anndata.AnnData.uns` ``['gearyC']`` - the above mentioned dataframe, if ``mode = {sp.GEARY.s!r}``.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     _assert_connectivity_key(adata, connectivity_key)
 
     def extract_X(adata: AnnData, genes: str | Sequence[str] | None) -> tuple[NDArrayA | spmatrix, Sequence[Any]]:
@@ -352,6 +360,7 @@ def co_occurrence(
     n_jobs: int | None = None,
     backend: str = "loky",
     show_progress_bar: bool = True,
+    table_key: str = "table",
 ) -> tuple[NDArrayA, NDArrayA] | None:
     """
     Compute co-occurrence probability of clusters.
@@ -369,6 +378,9 @@ def co_occurrence(
         Number of splits in which to divide the spatial coordinates in
         :attr:`anndata.AnnData.obsm` ``['{spatial_key}']``.
     %(parallelize)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -383,7 +395,11 @@ def co_occurrence(
     """
 
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     _assert_categorical_obs(adata, key=cluster_key)
     _assert_spatial_basis(adata, key=spatial_key)
 

src/squidpy/gr/_ripley.py

@@ -39,6 +39,7 @@ def ripley(
     n_steps: int = 50,
     seed: int | None = None,
     copy: bool = False,
+    table_key: str = "table",
 ) -> dict[str, pd.DataFrame | NDArrayA]:
     r"""
     Calculate various Ripley's statistics for point processes.
@@ -93,6 +94,9 @@ def ripley(
         Number of steps for the support.
     %(seed)s
     %(copy)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -105,7 +109,11 @@ def ripley(
     or :cite:`Baddeley2015-lm`.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     _assert_categorical_obs(adata, key=cluster_key)
     _assert_spatial_basis(adata, key=spatial_key)
     coordinates = adata.obsm[spatial_key]

src/squidpy/gr/_sepal.py

@@ -43,6 +43,7 @@ def sepal(
     n_jobs: int | None = None,
     backend: str = "loky",
     show_progress_bar: bool = True,
+    table_key: str = "table",
 ) -> pd.DataFrame | None:
     """
     Identify spatially variable genes with *Sepal*.
@@ -79,6 +80,9 @@ def sepal(
         Whether to access :attr:`anndata.AnnData.raw`.
     %(copy)s
     %(parallelize)s
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -94,7 +98,11 @@ def sepal(
     consider re-running the function with increased ``n_iter``.
     """
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
     _assert_connectivity_key(adata, connectivity_key)
     _assert_spatial_basis(adata, key=spatial_key)
     if max_neighs not in (4, 6):

src/squidpy/tl/_sliding_window.py

@@ -25,6 +25,7 @@ def sliding_window(
     spatial_key: str = "spatial",
     drop_partial_windows: bool = False,
     copy: bool = False,
+    table_key: str = "table",
 ) -> pd.DataFrame | None:
     """
     Divide a tissue slice into regulary shaped spatially contiguous regions (windows).
@@ -46,6 +47,9 @@ def sliding_window(
         If True, drop windows that are smaller than the window size at the borders.
     copy: bool
         If True, return the result, otherwise save it to the adata object.
+    table_key
+        Key in :attr:`spatialdata.SpatialData.tables` where the table is stored.
+        Only used if ``adata`` is a :class:`spatialdata.SpatialData`.
 
     Returns
     -------
@@ -56,7 +60,11 @@ def sliding_window(
         raise ValueError("Overlap must be non-negative.")
 
     if isinstance(adata, SpatialData):
-        adata = adata.table
+        if table_key not in adata.tables:
+            raise ValueError(
+                f"Table '{table_key}' not found in SpatialData. Available tables: {list(adata.tables.keys())}"
+            )
+        adata = adata.tables[table_key]
 
     # we don't want to modify the original adata in case of copy=True
     if copy: